In a typical industrial setting, many types of rotating machinery are employed to provide the mechanical and other driving forces necessary for production. Over time, rotating and other structural elements of the machine degrade and fault conditions develop which may eventually lead to significant degradation of the machine's output or catastrophic failure of the machine. When a machine fault leads to stoppage of the machine, the resultant loss in productivity can be very costly to the company. Accordingly, proper maintenance of machinery is an important aspect of many industrial facilities.
Non-destructive, predictive maintenance of industrial machinery is often used to identify faulty machines so that machine "down-time" can be scheduled in a manner that minimizes any negative effect to manufacturing operations. Many predictive maintenance methods are employed to ascertain a machine's health. Arguably, the most effective analytical technique for identifying faults in rotating machinery involves the use of narrowband envelope alarm limits. By using an envelope alarm limit as a basis for which to compare a vibration spectrum, exceptions can be identified which are directly associated with specific fault conditions. Examples of such exceptions include individual spectral peaks which exceed the alarm limit envelope, and families of related peaks whose total energy exceeds the alarm limit envelope. The magnitude and frequency of these exceptions can be used by an analyst or an automated diagnostic system to identify the type and severity of a fault. In the past, exceptions analysis techniques have relied on alarm limits that are defined for certain frequency regions of the spectrum. One example is the case where a single alarm value is applied to the overall level of vibration of an entire spectrum. In this example, the energy of a given vibration spectrum is summed over the entire frequency region and compared to a single, overall alarm limit. Historically, vibration analysis software packages have also allowed the specification of separate frequency bands for which parameter values can be calculated. These parameter values can then be compared to their individual, separately defined alarm limit.
Many benefits are realized from the use of narrowband envelope alarming (NEA). The NEA approach allows the analyst to maintain maximum sensitivity to all types of fault conditions (e.g., high power, low power, etc.) anywhere in the frequency range. In contrast, broadband analysis techniques can easily mask certain types of faults. Narrowband envelope alarming provides better diagnosis and identification of faults since it identifies precise frequencies at which an anomalous condition is occurring, which is the basis of an accurate diagnosis of the fault condition. Additionally, NEA produces data which can be analyzed to obtain a more accurate assessment/valuation of fault severity.
While many benefits can be realized from the use of an NEA technique, there are also substantial difficulties and disadvantages associated with currently known NEA techniques. For example, establishing individual alarm values manually for every envelope window is a very tedious (if not impossible), labor-intensive process, and there is no accepted methodology for creating the envelope limits. Even computer-assisted methods of determining a narrowband envelope can require tremendous amounts of data over a complete range of operational states to be monitored, and the required data will typically have to be acquired during manual periodic survey programs over extended periods of time. Moreover, there is currently no well-established method for turning the population of data into effective narrowband envelopes.
An inappropriate NEA will generate many false alarms. False alarms can result since there are many variables being tested and the process is highly dependent on accurate RPM values for each spectrum, which are commonly not measured when the spectrum is collected. Additionally, purely statistical methods for performing NEA can be easily corrupted by the inclusion of bad data (i.e., spectra representing fault conditions) in the analyzed population.
The many pitfalls and enormous labor involved with constructing appropriate narrowband envelopes has prevented, or at least significantly limited, application of NEA techniques by vibration analysis practitioners. Accordingly, what is needed is a method and apparatus for easily and effectively developing accurate narrowband envelopes for identification of faults in rotating machinery, regardless of the amount of historical spectral vibration data that is available to construct the narrowband envelope.